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Sygaldry Technologies

Provides quantum-accelerated AI server infrastructure

Quantum-AI Postdoctoral Fellow

AI ResearchConfirmed live in the last 24 hours
Full-time$125k - $145k

About the Job

Requirements

  • Hold a PhD, or be nearing completion, in Computer Science, Physics, Applied Mathematics, or a related field.
  • Have deep expertise in diffusion probabilistic models, score matching, or related generative methods.
  • Understand the mathematical foundations of stochastic differential equations, ordinary differential equations, Langevin dynamics, and probability flow.
  • Have experience with machine-learning frameworks such as PyTorch and JAX and write clean, research-grade code.
  • Have a strong record of research excellence, including first-author publications.

Responsibilities

  • Investigate and advance state-of-the-art diffusion and score-based generative models, focusing on mathematical efficiency.
  • Conduct theoretical analysis of computational bottlenecks in sampling, denoising, and likelihood estimation.
  • Develop novel solver methods for diffusion ordinary and stochastic differential equations that are mathematically compatible with quantum algorithms.
  • Identify mathematical structures in generative models, such as linear algebra subroutines and probabilistic flows, that may be suitable for quantum speedup.
  • Prototype hybrid workflows in which quantum subroutines accelerate classical pipelines, using simulation or hardware access.
  • Benchmark theoretical versus practical advantages and produce white papers and internal technical reports.
  • Publish findings in top-tier conferences and journals.
  • Collaborate with quantum hardware teams to inform future architecture requirements based on algorithmic needs.
  • Translate research insights into scalable proof-of-concept implementations for handoff to engineering teams.

Desired Qualifications

  • Published research specifically on diffusion models, score-based generation, or neural ordinary/stochastic differential equation methods.
  • Experience optimizing sampling efficiency, including methods such as DDIM, DPM-Solver, or consistency models.
  • Familiarity with numerical methods for differential equations.
  • Understanding of quantum algorithms and computational complexity; deep quantum expertise is not required if machine-learning mathematics is strong.
  • Background in high-dimensional probability or stochastic processes.

About the Company

Sygaldry Technologies

Provides quantum-accelerated AI server infrastructure

Sygaldry Technologies builds quantum-accelerated AI servers that bring quantum capabilities into AI models and workflows. It achieves this by integrating multiple qubit modalities within a fault-tolerant architecture to form utility-scale quantum computers that accelerate training and inference. Unlike others that rely on a single quantum technology, Sygaldry combines diverse qubit approaches in a single platform to tailor performance. Its goal is to provide affordable, sustainable, personalized, and secure superintelligence through practical quantum AI infrastructure.

Company size
11-50
Company stage
Series A
Total funding
$139.1M
Headquarters
Ann Arbor, MI
Founded
2024

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